Can marine protected areas alleviate poverty in the context of land desertification? – MPA-POVERTY

The project is built around two strong beliefs: (i) remote-sensing data analyses through artificial intelligence have the potential to revolutionize ecological and social science and (ii) marine protected areas can sustain both biodiversity and human well-being in the context of land desertification imperiling rural agriculture. The project is also transdisciplinary between social, environmental, ecological and computer sciences.

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The impacts of future climatic conditions on agriculture and marine fisheries are expected to be widespread, complex, geographically variable, and mostly unfavorable, particularly in tropical countries where human development and health are of serious concern. Here we hypothesize that coastal towns and villages close to marine protected areas (MPAs) can better alleviate poverty in the context of land desertification than their counterparts without any management action on nearby marine ecosystems. We propose to test the link between biodiversity protection and economic development over a long time period (up to 20 years) by combining the most up-to-date (i) spatially gridded socioeconomic information, (ii) satellite imagery analyses, (iii) artificial intelligence and (iv) in situ observations in developing countries of the Mozambique channel. We will follow a data-to-model-to-decision-making process where ‘putting fish back to the menu’ is a potential transformation pathway. Six main objectives will be reached within 5 years:
1. Delineating and characterizing all coastal and rural socio-ecological systems (CRSES) on the coasts of Madagascar, Comoros, Mozambique, Kenya and Tanzania
2. Sampling of representative coastal and rural socio-ecological systems in the Mozambique Channel
3. Estimating socioeconomic outcomes in the selected coastal and rural socio-ecological systems
4. Testing the hypothesis that proximity to a locally managed marine protected area can improve human economic development and health in the context of land desertification
5. Identifying, visiting and understanding the ‘bright’ vs. the ‘dark’ spots, i.e. the coastal and rural socio-ecological systems with the highest vs. lowest level of economic development and health
6. Dissemination our findings and transformative solutions to local managers, stakeholders and governments

The project is built around two strong beliefs: (i) remote-sensing data analyses through artificial intelligence have the potential to revolutionize ecological and social science and (ii) marine protected areas can sustain both biodiversity and human well-being in the context of land desertification imperiling rural agriculture. The project is also transdisciplinary between social, environmental, ecological and computer sciences. It lies at the cross-road of five U.N. 2030 Sustainable Development Goals (SDGs): eliminating poverty (SDG1) and hunger (SDG2), reducing inequalities among countries (SDG10), mitigate climate impacts (SDG13) while conserving and sustaining the long-term use of oceans, seas and marine resources (SG14).